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    CONVOLUTIONAL NEURAL NETWORK (CNN) PROCESSING METHOD AND APPARATUS
    1.
    发明申请
    CONVOLUTIONAL NEURAL NETWORK (CNN) PROCESSING METHOD AND APPARATUS 有权

    公开(公告)号：US20230051648A1

    公开(公告)日：2023-02-16

    申请号：US17975837

    申请日：2022-10-28

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Jinwoo SON ,  Changyong SON ,  Jaejoon HAN ,  Chang Kyu CHOI

    IPC: G06N3/04 ,  G06N3/08

    Abstract: Disclosed is a convolutional neural network (CNN) processing apparatus and method, the apparatus configured to determine a loading space unit for at least one loading space in an input based on a height or a width for an input feature map of the input and an extent of a dimension of a kernel feature map, load target input elements corresponding to a target loading space, among the at least one loading space, from a memory and store the target input elements in an allocated input buffer having a size corresponding to the loading space unit, and perform a convolution operation between the target input elements stored in the input buffer and at least one kernel element of a kernel.

    NEURAL NETWORK METHOD AND APPARATUS
    2.
    发明申请
    NEURAL NETWORK METHOD AND APPARATUS 有权

    公开(公告)号：US20220138576A1

    公开(公告)日：2022-05-05

    申请号：US17574408

    申请日：2022-01-12

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Changyong SON ,  Jinwoo SON ,  Byungin YOO ,  Chang Kyu CHOI ,  Jae-Joon HAN

    IPC: G06N3/08 ,  G06F5/01 ,  G06N3/063 ,  G06F7/523 ,  G06N3/04

    Abstract: A lightened neural network method and apparatus. The neural network apparatus includes a processor configured to generate a neural network with a plurality of layers including plural nodes by applying lightened weighted connections between neighboring nodes in neighboring layers of the neural network to interpret input data applied to the neural network, wherein lightened weighted connections of at least one of the plurality of layers includes weighted connections that have values equal to zero for respective non-zero values whose absolute values are less than an absolute value of a non-zero value. The lightened weighted connections also include weighted connections that have values whose absolute values are no greater than an absolute value of another non-zero value, the lightened weighted connections being lightened weighted connections of trained final weighted connections of a trained neural network whose absolute maximum values are greater than the absolute value of the other non-zero value.

    FACE VERIFICATION METHOD AND APPARATUS
    4.
    发明申请
    FACE VERIFICATION METHOD AND APPARATUS 有权

    公开(公告)号：US20210089755A1

    公开(公告)日：2021-03-25

    申请号：US17111912

    申请日：2020-12-04

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Changyong SON ,  Wonsuk CHANG ,  Deoksang KIM ,  Dae-Kyu SHIN ,  Byungin YOO ,  Seungju HAN ,  Jaejoon HAN ,  Jinwoo SON ,  Chang Kyu CHOI

    IPC: G06K9/00 ,  G06K9/78 ,  G06K9/62

    Abstract: Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.

    NEURAL NETWORK METHOD AND APPARATUS
    6.
    发明申请
    NEURAL NETWORK METHOD AND APPARATUS 审中-公开

    公开(公告)号：US20180032866A1

    公开(公告)日：2018-02-01

    申请号：US15630610

    申请日：2017-06-22

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Changyong SON ,  Jinwoo SON ,  Byungin YOO ,  Chang Kyu CHOI ,  Jae-Joon HAN

    IPC: G06N3/08 ,  G06F7/523 ,  G06F5/01 ,  G06N3/04

    CPC classification number: G06N3/08 ,  G06F5/01 ,  G06F7/523 ,  G06N3/04 ,  G06N3/063 ,  G06N3/082

    Abstract: A lightened neural network method and apparatus. The neural network apparatus includes a processor configured to generate a neural network with a plurality of layers including plural nodes by applying lightened weighted connections between neighboring nodes in neighboring layers of the neural network to interpret input data applied to the neural network, wherein lightened weighted connections of at least one of the plurality of layers includes weighted connections that have values equal to zero for respective non-zero values whose absolute values are less than an absolute value of a non-zero value. The lightened weighted connections also include weighted connections that have values whose absolute values are no greater than an absolute value of another non-zero value, the lightened weighted connections being lightened weighted connections of trained final weighted connections of a trained neural network whose absolute maximum values are greater than the absolute value of the other non-zero value.

    FACE VERIFICATION METHOD AND APPARATUS
    8.
    发明申请
    FACE VERIFICATION METHOD AND APPARATUS 有权

    公开(公告)号：US20210089754A1

    公开(公告)日：2021-03-25

    申请号：US17111907

    申请日：2020-12-04

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Changyong SON ,  Wonsuk CHANG ,  Deoksang KIM ,  Dae-Kyu SHIN ,  Byungin YOO ,  Seungju HAN ,  Jaejoon HAN ,  Jinwoo SON ,  Chang Kyu CHOI

    IPC: G06K9/00 ,  G06K9/78 ,  G06K9/62

    Abstract: Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.

    NEURAL NETWORK METHOD AND APPARATUS
    9.
    发明申请
    NEURAL NETWORK METHOD AND APPARATUS 审中-公开

    公开(公告)号：US20200005146A1

    公开(公告)日：2020-01-02

    申请号：US16564494

    申请日：2019-09-09

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Changyong SON ,  Jinwoo SON ,  Byungin YOO ,  Chang Kyu CHOI ,  Jae-Joon HAN

    IPC: G06N3/08 ,  G06F5/01 ,  G06F7/523 ,  G06N3/04

    Abstract: A lightened neural network, method, and apparatus, and recognition method and apparatus implementing the same. A neural network includes a plurality of layers each comprising neurons and plural synapses connecting neurons included in neighboring layers. Synaptic weights with values greater than zero and less than a preset value of a variable a, which is greater than zero, may be at least partially set to zero. Synaptic weights with values greater than a preset value of a variable b, which is greater than zero, may be at least partially set to the preset value of the variable b.

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